Crowd Data Visualization and Simulation

Simulating large and complex urban environments for real-time simulation poses multiple challenges which are not trivial to solve, for instance, gathering information of geometry for cities to be displayed, management of large quantities of data and fetching efficiently the information needed for the simulation and visualization of virtual pedestrians are just some examples of the challenges we face. In this work we present the results we have achieved so far using a system that addresses problems such as data visualization using level of detail techniques, GPU processing for efficient computation and the integration of real data into the simulation such as GPS data and real 3D cities that are generated using tools such as WRLD-3D plug-in. This method has been proven powerful enough to handle large crowds composed by thousands of agents in urban environments at interactive frame rates (at least 30 frames per second or 33.33 ms per frame) without compromising the visual quality and the complexity of the behaviors by using publicly real world data such as city topography and pedestrian GPS data.